GCRI · Campaigns
Risk literacy
Risk literacy is the ability to find, understand and weigh information about uncertain harms: a forecast probability, a relative risk in a health headline, a flood map, a return period. It depends on numeracy, on how the information is presented and on whether the source is trusted. This page sets out how understanding of risk forms and fails, how it is measured, which presentation choices the research supports, and what the evidence can and cannot tell the educators and agencies who design risk information.
Risk literacy in seven parts.
- 01The questionRisk literacy: how the risk develops
- 02In the five domainsRisk literacy helps people act on each domain’s warnings
- 03IndicatorsWhat is measured, and how well
- 04SourcesWhere the evidence comes from
- 05DecisionsWho decides, and what the evidence serves
- 06Core questionsWhat experts ask
- 07MechanismsWhat drives the outcome
Risk literacy: how the risk develops.
Teaching complex risks with clear evidence. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Formats shape understanding
The same evidence reads differently as a relative risk, an absolute risk or a natural frequency. Probabilities without a reference class, such as a chance of rain with no stated area or period, are routinely misread. Icon arrays and frequencies reduce some errors; they do not remove them.
Feeling runs ahead of numbers
People judge risk through affect, familiarity and vivid examples as well as probability. Hazards that are dreaded, involuntary or unfamiliar feel larger than common ones. These judgements are not simply errors: they carry values, such as fairness and control, that technical estimates leave out.
Trust filters the message
Whether a message is believed depends on who sends it, their perceived competence and honesty, and the audience’s prior views. Where institutional trust is low, accurate information from an authority source can be discounted while confident claims from familiar voices travel further.
Distortion amplifies and cascades
Headlines, shares and commentary amplify some risks and attenuate others, as the social amplification of risk framework describes. A misreading repeated across outlets becomes the common understanding, and corrections usually arrive later and reach fewer people than the original claim.
Connected activity in South Asia.
Population density, night lights and flood water over South Asia, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Connected activity, for this page
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
- Provider
- NASA LAADS DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite radiance, corrected for moonlight and atmosphere
- Newest at build
- 2026-10-12
- Resolution
- about 500 m grid
- Uncertainty
- Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- VIIRS Global Flood Product (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite detection; clouds leave gaps. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Estimated
- Source
- GPM IMERG (NASA GES DISC)
- Provider
- NASA GES DISC
- Licence
- NASA open data
- Vintage
- daily; Satellite estimate, near real time
- Newest at build
- 2026-10-12
- Resolution
- about 2 km grid
- Uncertainty
- Satellite estimate, near real time. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Connected activity, framed on South Asia.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA/NOAA VIIRS · NASA JPL OPERA DIST-ALERTSources and licences
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- GPM IMERG precipitation, NASA Precipitation Processing System; distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Observed (EO): NASA/NOAA VIIRS (Suomi NPP). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Optional layers (5 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026
Risk literacy helps people act on each domain’s warnings.
- WaterIn practiceUnderstanding what a flood warning level means.What a reader can checkComprehension tests
- HealthIn practiceUnderstanding heat-health advice.What a reader can checkBehaviour during heat
- FoodIn practiceUnderstanding price and supply information.What a reader can checkUse of market information
Evaluations are designed for the Evidence Brief series. Risk communication follows WHO guidance (2017); literacy measures are reported with their instruments.
- Survey instruments and results.
- Co-designed materials.
Campaign wave tracker.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Campaign wave tracker
Risk literacy · Wave 2 · Campaign area North
- People reached126929Active
- Consent complete, % of participants100Normal
- Knowledge score change0.3pointsNormal
- Open feedback items4Watch
Preparedness actions by area
Messages under test
| Prepare a water reserve | A | 36 | Revise |
| Know your warning levels | B | 56 | Revise |
| Check on neighbours | A | 39 | Keep |
Safeguarding and consent
- S-1Minor enrolled without guardian recordPause and verify2 d
- S-2Withdrawal requestData deleted, logged3 d
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Numeracy score | points on a validated scale such as the Berlin Numeracy Test | per study | Standardised test in audience research | OBSERVED |
| Correct interpretation of a probability statement | percent of tested participants | per study | Comprehension task with the item stated | OBSERVED |
| Self-assessed understanding of local hazards | percent of respondents | per survey wave | World Risk Poll and national surveys | REPORTED |
| Trust in scientists | index score | per survey wave | Wellcome Global Monitor | REPORTED |
| Adult literacy and numeracy proficiency | distribution across proficiency levels | per survey cycle | OECD Survey of Adult Skills | Published statistics |
| Readability of published material | grade level by a named formula | per release | Readability assessment of text | ESTIMATED |
| Accessibility conformance | WCAG success criteria met, by level | per release | Accessibility audit | OBSERVED |
| Reach of explainer material | unique readers per release | monthly | Consent-based web analytics | ESTIMATED |
A threshold model of collective behaviour.
Each agent acts once enough of its contacts have; small changes in the mean threshold or the early movers decide whether the behaviour stays local or cascades through the population. Teaching model with stated illustrative values, not a prediction. The map on this page shows South Asia; the model itself is not tied to a place.
Controls
- Mean threshold (share of neighbours)
- 18%
- Spread of thresholds
- 8 points
- Early movers
- 2.0% of people
- Contacts per person
- 8
Readouts
- Share who acted in the end
- 100%
- Global cascade
- Yes
- Steps to settle
- 11
Numbers, methods and sources
| Step | Share who have acted (%) |
|---|---|
| 0 | 1.3 |
| 1 | 6.0 |
| 2 | 17.8 |
| 3 | 32.8 |
| 4 | 48.3 |
| 5 | 64.5 |
| 6 | 78.8 |
| 7 | 89.0 |
| 8 | 96.5 |
| 9 | 99.3 |
| 10 | 100.0 |
| 11 | 100.0 |
Methods
- Threshold models of collective behaviour Granovetter (1978), American Journal of Sociology 83
- Global cascades on random networks Watts (2002), PNAS 99
- Complex contagions Centola and Macy (2007), American Journal of Sociology 113
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme’s own evidence.
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Campaigns in Foundry
- Tested at Campaigns in Universe
- Codified in Governance, Security and Society in Standards
- Published in Campaigns in Reports
- Taught in Faculty of Governance, Policy and International Affairs in Academy
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| Lloyd’s Register Foundation World Risk Poll | Nationally representative survey of risk perception, experience of harm and preparedness across many countries | Free to use with attribution |
| Wellcome Global Monitor | Trust in science and scientists, understanding of science and sources of health information | Free to use with attribution |
| OECD Survey of Adult Skills (PIAAC) | Adult literacy, numeracy and problem-solving proficiency by country and group | OECD terms; public-use files free, restricted files by licence |
| OECD PISA | Reading, mathematics and science literacy of fifteen-year-olds, including reading in digital environments | OECD terms, free with attribution |
| Reuters Institute Digital News Report | News use, trust in news and platforms, and concern about false information by country | Free to read; survey data by request |
| Special Eurobarometer surveys on science and technology | Public knowledge of and attitudes to science across EU member states | Free reuse with attribution; microdata through GESIS |
| Harding Center for Risk Literacy fact boxes | Worked formats for presenting benefits and harms as natural frequencies | Free to read; reuse per terms |
Model risk literacy as a system. Run the cascade.
Assembled from the Nexus Standards area profile Information integrity and trust: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
- Civil unrest
- Ice-jam flood
- Tropical cyclone
- Heatwave
- HIV epidemic
- Dam failure
- Storm surge (set off downstream)
- Intense rainfall (set off downstream)
- River flood (set off downstream)
- Flash flood (set off downstream)
- Dangerous surf (set off downstream)
- Widespread power outage (set off downstream)
- Mass displacement (set off downstream)
- Coastal flood (set off downstream)
- Extreme fire weather (set off downstream)
- Wildfire (set off downstream)
- Heat-driven grid stress (set off downstream)
- Agricultural drought (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-2Citation and attribution format for UNIsNS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-12Software, model and AI/ML artefacts (supply chain, model cards, dataset sheets)NRS-H52Hazard family: Information-integrity attacks (NHS-1 cyber.integrity)NRS-X7Information integrity and public trustNRS-U23Universe platform profile: ReportsNRS-A4Zero-trust verification of standards and conformanceNRS-H65Hazard family: Planetary boundary transgressions (NHS-1 planet.boundary)NRS-H72Hazard family: Novel entities and emerging contaminants (NHS-1 poll.novel-entities)
Observation
- GDELT event database and global knowledge graph (listed for reference)
- Our World in Data datasets (listed for reference)
- Number of countries that adopt and implement guarantees for public access to information
Example geography
- The Horn of Africa: 253 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface air temperature, daytime (AIRS), NASA GIBS
Who decides, and what the evidence serves.
Campaigns prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Ministries of education and curriculum authorities | Whether and where reasoning about risk and probability belongs in the curriculum, and for which ages | Adult and student proficiency data; comprehension studies of the formats taught |
| Public health agencies | How to present the benefits and harms of a screening programme or vaccine | Format comparison evidence; trust data by group; tested materials |
| National meteorological and hydrological services | How to word probabilistic forecasts and impact-based warnings | Comprehension tests of probability wording; audience research on common misreadings |
| Newsroom editors and science desks | How to report relative and absolute risk and the uncertainty of a study | Format guidance, glossaries and documented examples of misreading |
Outputs this topic produces
- Campaign explainers that state the evidence, its label and its uncertainty in plain language
- Presentation formats for probabilities and return periods, with their comprehension test records
- Glossaries of risk terms in the languages of the intended audience
- Accessibility and readability reviews published with each explainer
How risk literacy is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
System model
The couplings between the systems in risk literacy: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
What experts ask.
- 01
What do people need to know to act?
Which pieces of a risk assessment change a decision, and which are detail that can be left out without misleading.
- 02
How should uncertainty be shown?
Whether ranges, scenarios or plain statements of confidence help people decide, and when they confuse.
- 03
Who is the message for?
How prior knowledge, language, numeracy, culture and trust differ across the intended public.
- 04
Does the material work?
Whether people understand the risk better afterwards, and whether that understanding lasts.
What drives the outcome.
Research on risk perception shows systematic patterns. People judge risks by how dreadful, familiar, controllable and fair they seem, not only by how likely they are. Rare, vivid events are overestimated and chronic, diffuse risks underestimated. Relative risks (“twice as likely”) are easily misread without the baseline they refer to.
Presentation matters as much as content. Natural frequencies (“one in a hundred households”) are generally easier to reason with than conditional probabilities. Visual displays can clarify or distort depending on scale and framing. Messages that state what is known, what is not and what a person can do tend to sustain trust better than messages that project certainty and later need correcting.
Trust is the multiplier. The same evidence lands differently when it comes from a source the audience regards as competent, honest and on its side.
How evidence is gathered, and where it stops.
| Method | What it shows | Its limit |
|---|---|---|
| Audience research | Prior knowledge, misconceptions and preferred formats | Small samples may not represent every group |
| Comprehension testing | Whether material is understood as intended | Understanding in a test is not behaviour in life |
| Pre and post surveys | Change in knowledge or confidence | Self-report and attrition bias |
| Expert review | Accuracy and fair statement of uncertainty | Experts can disagree; disagreement is recorded |
How it is studied, and what the methods cannot say.
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
Is risk literacy the same as numeracy?
Why use natural frequencies?
Are people bad at understanding risk?
Does Campaigns issue risk advice?
Which values on this page are real?
Is risk literacy about teaching statistics?
Can a campaign tell people how dangerous something is?
How is success judged?
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